Artificial Intelligence: Introduction to AI

Privacy

Many AI systems ask users to consent to the program using and accessing personal data in ways they may or may not understand. Consider the “Terms & Conditions” often shared when downloading a new software. Users may just click “Accept” without fully reading and digesting how their data may be used. Or, if they do read and understand it, there are other layered ways the program could be using their data, like the system knowing their location. Moreover, if platforms are required as part of curricula, some argue parents and children are being “forced” to share their data.

Surveillance

AI systems may also follow how a user is interacting with things; the resulting experience provides a personalized experience. In education, this may include systems identifying strengths, weaknesses, and patterns in a students’ performance. While teachers do this to some degree in their teaching, Akgun and Greenhow say, “monitoring and tracking students’ online conversations and actions also may limit [student] participation … and make them feel unsafe to take ownership for their ideas.”

Autonomy

Because AI systems rely on algorithms—such as predicting how a student may perform on a test—students and teachers may find it difficult to feel independence in their work. It also, the scholars say, “raise[s] questions about fairness and self-freedom.”

Bias and discrimination

These factors can appear in a variety of ways in AI systems like through gendered language translation (“She is a nurse,” but “he is a doctor”). Whenever algorithms are created, the scholars say, the makers also build “a set of data that represent society’s historical and systemic biases, which ultimately transform into algorithmic biases. Even though the bias is embedded into the algorithmic model with no explicit intention, we can see various gender and racial biases in different AI-based platforms.”

Retrieved from Exploring the ethics of artificial intelligence in K-12 education